Prediction of the Rate of Penetration while Drilling Horizontal Carbonate Reservoirs Using the Self-Adaptive Artificial Neural Networks Technique

Prediction of the Rate of Penetration while Drilling Horizontal Carbonate Reservoirs Using the Self-Adaptive Artificial Neural Networks Technique

Rate of penetration (ROP) is one of the most important drilling parameters for optimizing the cost of drilling hydrocarbon wells. In this study, a new empirical correlation based on an optimized artificial neural network (ANN) model was developed to predict ROP alongside horizontal drilling of carbo...

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Bibliographic Details
Main Authors: Ahmad Al-AbdulJabbar, Salaheldin Elkatatny, Ahmed Abdulhamid Mahmoud, Tamer Moussa, Dhafer Al-Shehri, Mahmoud Abughaban, Abdullah Al-Yami
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Sustainability
Subjects:
rate of penetration
drilling optimization
carbonate reservoir
horizontal wells
Online Access:https://www.mdpi.com/2071-1050/12/4/1376

Internet

https://www.mdpi.com/2071-1050/12/4/1376

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